Bollinger on Bollinger Bands by John Bollinger

We live in a relative world. There are no absolutes for determining if a person is rich, smart, or good looking. Bollinger Bands define prices as relatively high or low and replace emotional decisions with a rational structured approach.

Bollinger recognizes markets are complex and everyone has different views on risk and reward. The following chapters offer tips on how to modify his analysis framework, to match individual preferences.

There are four types of price charts commonly used, line, bar, candlestick, and point and figure. Of the four, candlestick charts most effectively display the open, high, low, close and their relationship to each other. Bollinger, like many traders, prefer candlestick charts because of their simple clarity.

John Bollinger created Bollinger Bars as a cross between bar charts and candlestick charts. Like a candlestick price bar, the difference between the open and closing price is shown by the color of the bar.

If the close is lower than the open, the bar's section from the open to the closing price is colored red. If the close is higher than the open, this section is colored green. The rest of the bar is colored blue, for prices outside the open or close.

Whatever type of chart you use, there are two types of scaling, arithmetic or logarithmic (often called semi-log). With arithmetic scaling, a 1 point difference from 50 to 51 is the same vertical measure on a chart, as between 100 and 101. Yet 50 to 51 is a 2 percent increase while 100 to 101 is only 1 percent. Semi-log scaling keeps the price differences in a proportional relationship. A semi-log price bar of 50 to 51 would be twice the size as a bar from 100 to 101.

Bollinger usually prefers charts with Bollinger Bars and semi-log scaling. He highly recommends using semi-log scaling with whatever chart type you use.

It's important to include a stock's volume on the price chart, but not the raw volume totals. Instead, it's more useful to normalize the volume. To do this, divide each day's volume by a 50-day simple moving average of the daily volume. Multiply the result by 100 and plot this number on the chart. Add a horizontal reference line of 100.

Normalized volume shows when volume is relatively high or low, compared to its recent past. This also allows comparison to volume trends in other markets. What Bollinger Bands do for prices, normalization does for volume.

Like other market aspects, time period classification is relative. An investor's long term could be four years and a day trader's long term four hours. But both can classify their time frames as short, intermediate, and long term.

The long term time frame can be used for overall background analysis. For an investor, this might be the underlying economic conditions. For a trader, the long term time frame corresponds to the major price trend.

The intermediate time frame narrows the focus to market specifics. For a trader, this could mean noting price or volume patterns which indicate a possible trade. The investor might want to see which sectors were showing the most strength in the intermediate time frame.

Short term time frames are for trade execution. Both the investor and trader will use some tool or price pattern to signal an entry.

Each time frame has a different purpose and it's important to keep them separate. If you switch activities from one time frame to another, it muddles the process. And a muddled process only leads to confusion and poor decision making.

Bollinger Bands can be used in all three time frames, but need adjustment to fit each one. The adjustment can be the bar's time period, the moving average length, or the width of the bands.

The base period for Bollinger Bands should be the intermediate time frame. If a daily chart was the intermediate time frame, then the standard default values could be used. These values are a 20-day moving average with 2 standard deviations for the bands.

The default values usually work well, but consider them as a starting point when making adjustments. If choosing a different period for the moving average, look for one which shows support for price reactions, especially the first reaction after a trend change.

If a different period is used, also change the standard deviation number. For a period of 10 bars, try 1.5 standard deviations and 2.5 standard deviations for a 50 bar period. [Chapter 7 changes these suggested values to 1.9 standard deviations for 10 periods and 2.1 for 50 periods.]

Market characteristics change over time. Any trading or investing approach, must be able to adapt. Switch funds seek to adapt by continuously recreating an ideal portfolio. This can succeed for a while, but at some point, the markets turn left while the fund turns right…into a loss.

The point is, no system or investing plan lasts forever. What is needed, is the ability to spot opportunities, where the potential reward, outweighs the risk. You have to pick the right stock at the right time. Bollinger Bands combined with other tools help find these favorable risk/reward situations.

The mark of a good tool or system, is its ability to work equally well with different parameter values. Any tools or methods you use, should be adjusted to fit your preferences. If you don't adapt your tools to suit your needs, you won't be comfortable using them. And trading is difficult enough without adding more stress.

It's said the first step to wisdom is to know yourself. If you want to be a successful trader or investor, you should be clear on the specific outcomes you want.

What do you want to achieve and what do you want to avoid? Do you have the patience and motivation to achieve your goals? Thinking for yourself and using discipline when following a trading plan is not easy to do. But if you want to win in the markets, it's required.

Before Bollinger Bands were created, traders used various types of bands, channels, and envelopes on their charts. Their purpose was to indicate high and low prices or price points to buy and sell.

The bands typically used a moving average as their basis. Either a set number of points, or a percentage of the moving average price, was used as an offset value. The offset value was added to the moving average to form the upper band and subtracted from the moving average for the lower band.

Envelopes like bands, enclose prices with upper and lower lines. They are not usually symmetrical and are often used to indicate the combination of market cycles.

Unlike bands and envelopes, channels have upper and lower parallel lines based on significant price points. Usually these prices are the important swing highs and lows for the time frame used.

A problem with these methods, is their inability to adjust to changes in volatility. Influenced by his work in options, in the early 1980s, John Bollinger decided to use volatility to set band widths.

Some of the initial testing used a fixed standard deviation value, to set percentage bands. It became clear, only a variable standard deviation value would be able to adapt to volatility changes. The solution was a moving average, which was the final piece needed in creating Bollinger Bands.

John Bollinger values relative relationships and adaptability. So it's no surprise these are two features of Bollinger Bands. Using market volatility to establish the band width, is what separates these bands from other methods. The long-term success of Bollinger Bands speaks to how valid this approach is.

The bands respond to price volatility by recording the difference between price bars and a moving average. It's a dynamic process which constantly changes with volatility.

To create the bands, calculate the standard deviation of the prices. Each bar's price is subtracted from the chosen period's average price and the results are squared. These differences are added and the total is divided by the number of price bars. The standard deviation is the square root of this number.

With the bands offset from a 20-period moving average by two standard deviations, about 89% of the prices should be contained within the bands. Longer and shorter moving averages, can be used with the standard deviation multiplier, lowered or raised along with the period.

It's recommended not to go below a 10 period average. Instead, shorten the time frame. Replace a short daily average with its equivalent hourly period average. In general, it's best to use a 20 to 30 period average.

Since their creation, various ways of modifying Bollinger Bands have been tried. The simple moving average was replaced with an exponential moving average. Or the period to calculate the volatility was different than the moving average period. But there has been no discernible advantage to any of the known modifications.

One modification which may be beneficial is multiple Bollinger Bands. One approach uses a single moving average with 2 or 3 different standard deviation multiplier values. The other multiple bands type uses 2 or 3 different moving averages with their appropriate standard deviation multiplier value.

While using multiple bands is an idea worth testing, it's recommended you first gain experience with the standard single 20-period bands.

Bollinger Bands give a visual reference for volatility, but also can supply numerical values. The first of two numerical indicators is %b. It is the proximity of price to the bands. The formula is:

(current price - lower BB) / (upper BB - lower BB)

When price touches the lower band, %b is 0. And for price touching the upper band, it's 1.

When price exceeds the upper or lower band, %b shows what percent of the band's width was exceeded. A %b reading of -1.2 represents a price below the lower band and the difference is 20 percent of the band's width.

The value of %b, is created by the constant relationship it provides between prices and band width. As volatility and band width changes, the relative relationship expressed by %b remains the same. This consistency of a numerical value allows %b to be used as a system parameter or in combination with other indicators.

BandWidth is the second indicator derived from Bollinger Bands. BandWidth relates the width of the bands to the moving average. The formula is:

(upper BB - lower BB) / middle BB.

Like %b, BandWidth offers an easy to chart numerical value. Tracking the BandWidth shows how the bands' width changes over time. The BandWidth number not only shows what has happened, but can indicate what will happen.

Volatility is constantly changing and when BandWidth registers a low number, a small band width, it implies the volatility will soon increase. This pattern is called, The Squeeze. And the simplest way to identify The Squeeze, is when BandWidth hits a six month low.

BandWidth has other patterns which can provide trend direction clues. If prices break out of a narrow range and BandWidth expands sharply, it's an indication of a sustained move. BandWidth can also indicate when a trend is ending. As volatility expands on an up or down move, if BandWidth flattens out or reverses, it's a sign the current leg of the move has ended.

Imagine you created a bar chart which showed the height differences for a large group of people. The chart's horizontal axis would be the height range from very short to very tall. The vertical axis would be the number of people for a given height.

The average height of the group would be at the chart's center. Most of the group would be slightly above, below, or equal to this average. The number of people taller and shorter than the average would decrease as the height difference increased. The resulting chart would resemble a bell-shaped curve.

The bell curve shape is characteristic of what's called a normal distribution. Many natural phenomenon are normally distributed, but not the daily price changes of stocks. Instead of a normal distribution, stocks have more large positive and negative price changes.

With more large price changes at the ends of the curve, there are fewer small price changes clustered around the average. The result of this distribution, is a flatter curve shape. The higher number of price-change extremes is sometimes referred to as the fat tail of the curve.

So what does this have to do with Bollinger Bands? Mainly to make the situation clear to those familiar with statistics.

A normal distribution has approximately 95 percent of a group's items, within 2 standard deviations of the group average. Because price changes are not normally distributed, the bands' 2 standard deviations contain about 89 percent of the price changes, instead of 95.

Another way in which Bollinger Bands differ from statistical expectations, is for price change regression to the mean. A series of extreme prices changes don't last forever. Eventually price action returns to the mean, which is the average price change.

Prices do regress to the mean, but not to the extent as expected with a normal distribution. This is why, when prices touch one of the outer bands, it doesn't mean prices will then return to the center. A return needs to be confirmed with an overbought/oversold type of technical indicator.

Prices usually move up and down in an irregular fashion, but volatility changes have a regularity which can be predicted. Volatility cycles from low to high and back again. These volatility changes, as shown by Bollinger Bands, can be used to improve the accuracy of price pattern analysis.

Apart from these minor exceptions, Bollinger Bands do follow general statistical concepts. This provides a basis for validating how they are constructed.

An important part of technical analysis is the ability to recognize important price behavior patterns. These patterns may indicate a reversal of a trend, or its continuation. But price patterns don't form in the exact same way each time. This makes it challenging to identify them as they occur. Technical indicators like Bollinger Bands, offer a way to help identify chart patterns.

Two common patterns which Bollinger Bands can help identify, are double bottoms and double tops. The general pattern shape is a "W" for double bottoms and an "M" for tops.

Typically, a double bottom has the prices of the first leg drop below the lower band, then retrace back to between the bands. The second leg of prices may or may not go lower than the previous price low, but ideally the price should remain within the bands. This action shows a loss of downward momentum and that the trend is indeed reversing.

The price action of double tops is the reverse of double bottoms. The first price spike is above the upper band, a sign of strong momentum. Then ideally, the second price peak is within the bands, due to a reduction in the upward momentum. A reduction in volume, as a top or bottom forms, helps confirm a reversal.

Bottoms, tops, and other patterns, form in all time frames and sometimes do so simultaneously. Price fractals are patterns in one time frame which is made up of the same pattern in a shorter time frame.

An aid to identifying price patterns is the use of a price filter. The filter reduces a pattern to its basic elements. When patterns are made more elemental, it's easier to compare them.

Prices can be filtered on the basis of a set number of points or a fixed percentage. When filtered this way, price swings are plotted only after moves of the defined points or percentage.

Using a percentage works better than points since it maintains relative relationships. A $10 stock might go up $5 to $15 in a year, but $100 stock might go up $5 in a week or a day. Using percentages, the major 50 percent move of the $10 stock would be matched by an equally major move of $50 for the $100 stock.

Another type of price filter is the point-and-figure chart. This type of chart records only price moves without respect to time. A one day series of swings could look the same as an equal number of price swings over a year.

A basic point-and-figure chart records a price swing in a single column. An "X" is added to the column as long as prices continue in the same direction. When prices reverse, the new swing is recorded in the next column over with Xs headed in the opposite direction.

Modern point-and-figure charts use Xs to record up swings and Os to record down swings. Each price level marked by an X or O is called a box. The problem with point-and-figure charts is the difficulty of scaling. If each box represents the same price move amount, moves at high and low price levels are out of proportion.

The most popular way to scale is to increase the box price amount in steps as price levels increase. Each box might represent a price change of 1 point when prices are between $20 and $100. Then a box might represent a price change of 2 points for prices over $100.

This stepped approach is an improvement, but the abrupt box price changes present a new problem. Price swings around a price level where box price amount changes, somewhat distorts those price swings.

To eliminate the price transition problem, Bollinger created Bollinger Boxes. After testing, Bollinger found a box should equal a move of 17 percent of the square root of the price. Bollinger Boxes provide a smooth transition through any price level.

Price filters make for more uniform price patterns but the patterns still need some kind of organization to be useful. In 1971, Robert Levy created a universal price classification based on five price points. Years later, Arthur A. Merrill expanded on the idea in his book, M & W Wave Patterns.

He divided all price movement into 32 patterns. Each pattern had five price points connected by four legs, which resembled Ws and Ms. Each W and M was identified with a number. Declining price patterns were given the lowest numbers and rising price patterns the highest numbers. The middle patterns: M6, M7, M8, M9, W6, W7, W8, and W9 represent variations of sideways price movement.

Deciding what does, or does not qualify as a common chart pattern, has always been a problem due to its subjective nature. But Merrill's organization allows classic chart patterns to be described as a series of Ms or Ws. This price filter changes the subjective to objective and a consistent basis for testing any pattern.

If prices are filtered with Bollinger Boxes to create the Ms and Ws, then their volatility can be used to forecast price moves.

Tops and bottoms are formed under opposite emotional conditions. When prices top, there's hope and excitement. When bottoms form, hope has been replaced by despair and pain. People give up more quickly when in pain than they will let go of hope. For this reason, bottoms often form more quickly than tops and are usually easier to recognize.

Not all price bottoms have the same shape. They can range from a sharp V formation to an extended period of sideways movement. But the most common type of pattern is the double bottom, also called a W bottom.

The W bottom comes in variety of forms. Each one is like a Rorschach test. The formation shows the dominant emotion which created the bottom.

If the second low of the bottom is higher than the first low, the major emotion is frustration. Traders expected prices to drop back to the first low. And now they're frustrated on missing out on the move up (see W4, W5, and W10).

When the two lows of a W bottom are equal, the frustrated traders of the previous example are feeling satisfied. The second low gave them the buying opportunity they were looking for.

A W bottom with the second low below the first low, is a situation with a high degree of fear. Traders who bought anywhere else in the formation, are now sitting on a loss. These traders are fearful because they're thinking this wasn't a bottom after all (see W2, W3, and W8).

Bollinger Bands can help confirm W bottoms when the second low is below the first. It's typical for any W bottom to have the second bottom be farther above the lower band than the first low was.

The interaction between price and the bands is a relative relationship. Even when the second low price is lower than the first, it's the low's proximity to the lower band that counts. In relation to the lower band, if the second low is higher than the first low, it's a sign a bottom has formed.

To confirm a W bottom, it makes no difference if the second price low is lower or higher than the first. it's only the relative position of the two lows in relation to the lower band that's relevant. This means if the second low is lower relative to the band than the first was, the bands offer no confirmation of a bottom. And in this case, stand aside.

When you find a W bottom that fits the pattern of a relatively higher second low, look to buy on strength. Get in on the first day off the low which has above average volume and a larger than average price range. Place an initial stop below the second low of the W and move it up as prices advance. Usually, make the stop tighter as profit increases.

Although the letter M is the inverse of the letter W, M tops are not an inverse of W bottoms. Tops tend to be more complex than bottoms and they often have three peaks before reversing the trend.

A head and shoulders is how one form of a triple-high top is often described. The middle of the three peaks is the highest of the three and is the "head". The peaks to either side are the "shoulders". The two lows between the shoulders and the head are usually at about the same level. A line drawn through these two lows is the "neckline" (see M15).

Upon completing the right shoulder, prices drop through the neckline. Shortly after this there's often a brief rally back to the neckline before continuing lower (see M1 or M3).

Volume is usually highest for the left shoulder, then falls off for the head, but picks up heading down off the right shoulder. Excitement and greed are the emotional drivers of the left shoulder. Often it's fueled by anticipation of some news. The news is good, which drives prices to a new high to form the head. Yet the news was expected, so volume drops as a result.

Optimists think they're getting a bargain when prices come down from the head. It's their buying which creates the right shoulder. But when that fails, fearful sellers push prices lower and volume picks up when the neckline is crossed.

Ideally, the left shoulder of a head and shoulders top should be above the upper Bollinger band. The head should just touch the top band and the right shoulder then forms well below the band.

The middle band (the moving average), intersects the neckline at the right shoulder. The initial decline off the shoulder ends when it reaches the lower band. Finally, the rally back to the neckline touches the middle band and then reverses. This final leg down breaks through the lower band.

That's the ideal formation sequence, but it's rare that a top will have all those characteristics. Use this description as a guide for the approximate price behavior in relation to the bands.

A variation of the head-and-shoulders is referred to as, "three pushes to the top". Usually this variation follows the normal head-and-shoulders type of interaction with the bands. The first peak, like the left shoulder, rises above the upper band. The next peak, like the head, makes a new high, but only touches the upper band. The final high, sometimes makes a new high, yet fails to reach the upper band. Volume decreases as the pattern progresses and so does the momentum.

A head-and-shoulders formation is a combination of the five-point price patterns of chapter 11. The M14 and M15 patterns, or a combination of the two, can create the left shoulder and head. From there, M3 and M4 or M7 and M8 would typically be the patterns for the right shoulder. Coming down off the right shoulder, M1 or M3 replicate the retracement rally back to the neckline.

For added confirmation of a top, look at a shorter time frame. There can be patterns in that time frame which may confirm a top has truly formed.

Once a top has formed, trade entry requires price weakness. Wait for a down day with volume and the daily price range both above their usual levels. Enter on that day or wait for a small retracement. A retracement, such as the rally back to the neckline, offers an excellent risk to reward opportunity.

One mistake traders make when using Bollinger Bands, is to see the bands as a simple overbought/oversold indicator. They think if price hits the upper band, it's a time to sell, or if the lower band, a time to buy. John Bollinger makes it clear, a tag of a band by itself, is not a signal of anything.

When prices are in a strong trend, they will often repeatedly touch the band on the left side. This behavior is called, walking the bands and it's a sign of trend continuation, not reversal. Some of the band touches may be the first part of a reversal pattern, but do not signal a reversal by themselves.

To analyze the trend when prices are walking the bands, volume indicators can be helpful. A running total of the Intraday Intensity Index (II) or the Accumulation Distribution (AD) indicator, provide good signals for trend direction.

II = [2 x close - high - low] / [(high - low) x volume]

AD = [(close - open) / (high - low)] x volume

The II and AD can also be measured over a set period instead of using a running total. With a running total, II and AD produce a gradually increasing or declining line. When the indicators measure only a fixed period, II and AD will usually move up and down in sync with the prices.

When prices are walking the bands and one of the indicators stops following prices as strongly as before, it's a sign of weakness. Usually there are one or more small divergences between price and the indicator before a more significant divergence indicates a trend reversal.

If a moving average is well matched to a stock's trend, it will often provide support or resistance to trend corrections. When walking the bands, if prices bounce off the Bollinger Bands' moving average, it's a sign the trend will continue. These points of contact are also an excellent entry point for the next leg in the trend.

When using other technical indicators as confirming tools, be objective but not rigid. If an indicator seems out of step with the price behavior, don't accept a confirmation signal.

Trading consistency requires thought and experience. How you use any indicator or system should be a match to your objectives for risk and investment return.

The Squeeze is a product of market volatility cycles. Bollinger Bands use this natural process to provide a trading opportunity.

BandWidth ({Upper BB - lower BB} / middle BB) measures how volatility compares to the average and is used to detect The Squeeze. A simple rule to identify The Squeeze is a BandWidth reading which is the lowest level for the last six months.

Once The Squeeze is in place, the only question is, which way will it break out. Volume and other indicators can provide a clue for the direction. A news item may provide the trigger.

In sports, a head fake is a motion to fool an opponent as to which way a player is going to move. When a market makes a head fake, you're the opponent getting fooled. Sometimes a a market will break out of The Squeeze in one direction and then quickly reverse in the true breakout direction.

There are two ways to deal with a head fake. The simplest is to avoid it. Hold off entry until a trend has is clearly established. But if waiting is not your style, you can enter on the breakout and simply reverse if necessary, with a stop-loss order.

The opposite of The Squeeze is The Expansion, when volatility becomes high. An important feature of The Expansion occurs when a strong trend first starts.

In an up move, the lower band will turn down as the volatility increases. In a down move, the upper band turns up with the initial period of increased volatility. When this expansion of the bands stops, it's a sign the current move has completed. Prices may reverse or pause in a sideways direction, before continuing the initial trend.

Volatility cycles, from periods of low price activity to periods of very active prices. The Volatility Breakout Method is based on this pattern. It uses The Squeeze, a period of low volatility, as the trade setup. The expectation is with a change from low to high volatility, there will be a strong up or down move.

The method was developed with daily charts, but it works on any time frame. You are encouraged to change any of the parameters to fit your trading style. Altering some aspect of a trading method to match your preferences, makes its successful use more likely.

The Volatility Breakout Method uses BandWidth (upper BB - lower BB) / middle BB) to provide the trade setup and entry signal. The BandWidth indicator determines when volatility is very low, and The Squeeze is present.

BandWidth uses the default parameters for Bollinger Bands of a 20-period average and 2 standard deviations. Short-term traders may want to decrease the parameters to a 15-period average and 1.5 standard deviations.

The Squeeze is indicated when BandWidth reaches a low for the previous 6 months. At that point wait for a strong move out of the current price range. But sometimes the first move is a false breakout. With experience, you'll find which markets do this more than others.

To avoid these false breakouts, known as head fakes, volume indicators such as the Intraday Intensity Index ([2 x close - high - low] / [(high - low) x volume]) or Accumulation Distribution ([(close - open) / (high - low)] x volume) can provide a clue as to the true breakout direction.

Two methods to exit a Volatility Breakout trade, are Welles Wilder's Parabolic, or a tag of the opposite band. Parabolic is a trailing stop which moves with every price change.

If using a band touch for the exit, it's the lower band when long and the upper band when short. The band touch exit usually results in larger profits since the trade is typically held longer than with Parabolic. The initial stop for either method is the side of the price range opposite the breakout.

The value of adding other technical indicators to Bollinger Bands is their ability to confirm or deny the validity of price patterns. When prices tag a band, a positive or negative indicator reading can provide an alert for a possible buy or sell opportunity.

A typical sequence of events when prices walk the bands, happens as follows. With each touch of the bands, an indicator maintains a strong reading, confirming the trend. As prices approach the eventual top or bottom, the indicator's signals become weaker with each new band touch. These weaker readings offer an alert that a reversal may be near.

Another situation in which an indicator can add value, is at tops and bottoms. Typically a new price high or low is made but not relative to the bands. If the band non-confirmation of the new price is also not confirmed by the indicator, it's a strong signal for a reversal.

Using multiple indicators for confirmation is also useful, but not if they rely on the same data. Use only one type of indicator for volume, momentum, overbought/oversold, or sentiment. An indicator for volume and one for sentiment make a good combination to use with Bollinger Bands.

Before starting to trade, pick one or more indicators you think will work well with Bollinger Bands. Test on old price charts or paper trade and select the ones you like best.

A string of losses always tests confidence in the trading method used. Testing your indicator choices before live trading, helps instill the confidence needed.

No indicator is perfect, so resist the urge to change indicators when there are some real-time false signals. An imperfect indicator is better than trying to find a perfect one for each trade.

Once you have decided on the Bollinger Band settings and indicators you'll use, create a chart layout of the combination. Use this as the template for the markets you follow. The template makes it simple to quickly scan all the charts looking for trade opportunities.

Optimization is a danger to be avoided with any indicator. Computers make it easy to find the parameter values which worked best for a set of data. But it's unlikely these values will do as well in real time.

If you decide to change parameter values, divide your data into sections before testing. Optimize in the first section and then test in every other section. if you get similar results, the values are probably reliable. An additional sign of reliability, is if parameter values close to what was chosen, also perform well.

A major premise for including volume when analyzing price behavior, is the concept of volume preceding price. When most volume comes before a major price move, it's a sign of smart investor behavior. They are either buying or selling in anticipation of a new trend. The importance of volume is why it's the first choice, when using an indicator with Bollinger Bands.

From Larry William's Accumulation Distribution to Buff Dormeier's Volume-Weighted MACD, there is no shortage of volume indicators. Of all the indicators, one of the most useful relates intraday or intraperiod price differences to volume. Another useful indicator group uses volume to modify an existing indicator.

Two indicators which track intraperiod changes are Intraday Intensity ([2 x close - high - low] / [high - low] x volume) and Accumulation Distribution ([(close - open) / (high - low)] x volume).

Intraday Intensity is a measure of how volume combined with a strong or weak close shows a strong or weak market. Accumulation Distribution matches volume with a comparison of the close and the open. Strong or weak markets are indicated by a close above or below the open.

Both indicators can be plotted as a cumulative total or as an oscillator covering a set length of time, usually 10 or 20 periods.

If using the oscillator format, it should be normalized so the readings are comparable from one market to another. To normalize the indicator, add up each individual rating for the chosen period. Divide that sum by the total volume over the period.

The other volume indicators of interest use volume to modify existing indicators. The Money Flow Index and the Volume Weighted MACD are two examples.

The Money Flow Index (MFI) adds volume to Welles Wilder's Relative Strength Index (RSI). MFI uses moving sums of price times volume to replace moving averages of price changes in RSI. This gives up or down days greater or lesser weight depending on higher or lower volume.

The Volume-Weighted MACD indicator modifies Gerald Appel's Moving Average Convergence Divergence (MACD). It replaces MACD's moving averages of price only, with volume weighted price averages. If volume does or does not support a trend, this modified MACD gives a corresponding stronger or weaker indication than the regular version.

Method II seeks to identify the start of a new trend. When prices move towards the upper or lower band, the Money Flow Index (MFI) is used to confirm the trend. This is similar to the Volatility Method, without The Squeeze.

A buy entry is signaled when %b is greater than 0.8 and MFI is greater than 80. The %b reading above 0.8 indicates prices are exceeding 80 percent of the band width. The MFI 80 indication shows market strength. Sell short signals are %b less than 0.2 and the MFI under 20.

The period for MFI is 10 or half the moving average period of the Bollinger Bands, if 20 isn't used. The default remains 2 standard deviations.

Exit either with a modified Welles Wilder's Parabolic or a touch of the band opposite the price trend. The modified Parabolic places the initial stop under the recent low or above the recent high, instead of using the entry day for placement.

An alternative entry technique, is to wait for the first reaction after the new trend starts. You'll miss out on some trades, but reduce whipsaws and usually have a lower initial risk.

In addition to adding technical tools to Bollinger Bands, fundamental factors can be included. Traders can make a list of prescreened strong or weak markets. Then only buy the strong and short the weak. This process has the same advantage as adding a technical indicator to help confirm signals.

The Reversals Method uses an indicator to show which band tags represent valid reversal points. The indicator used is either a pair of oscillators, or a modified MACD.

One oscillator of the pair, uses a 21-day and a 100-day moving average of the NYSE daily advances minus the declines. The oscillator is the result of the 100-day average subtracted from the 21-day average. The other oscillator is calculated in a similar fashion, but uses the NYSE daily up volume minus down volume for the two averages.

The difference of two moving averages can also be used to change the inputs for the MACD indicator. To do this, set the first MACD parameter to 21, the second to 100, and the signal line to 9. For one MACD inputs, use advances minus declines for the averages and up volume minus down volume for the second MACD plot.

Other indicators can be used to confirm bottom or top formations. If %b is higher for the second low (a relative W4 from chapter 12) of a W2 bottom, see if the Money Flow Index (MFI) or the Volume-Weighted MACD (VWMACD) confirm the pattern. Buy the first up day with high volume and a wide range if confirmed.

Tops are similar to bottom formation but the patterns take longer to complete. With tops you're looking for a progressively weaker %b with each new high. The volume indicator, Accumulation Distribution, will confirm the topping action by also registering weaker responses to the highs. Upon confirmation, look to short the first high volume wide range day, which closes down.

For the impatient, it's not always necessary to wait for a top or bottom to form. Instead, look for band tags with a volume indicator. When prices tag the upper band, the indicator should be low, showing price weakness.

When a tag is to the lower band, the indicator should show strength. %b coupled with a volume indicator, like Intraday Intensity, can create a mechanical system. Buys are made when %b is low, shorts when %b is high, and both confirmed by the indicator.

Bollinger Bands are more than a single use tool. Any data series can be used to create the bands, not just prices. The bands describe the relative high and low values of the data, regardless of what the data represents.

The Relative Strength Index (RSI) as commonly used, rates levels over 70 as overbought and under 30 as oversold. But these are averages. In a strong market 80 might work better than 70. Or 20 better than 30, in a very weak market. If instead of relying on fixed levels, you can plot Bollinger Bands around the RSI to give you better signals as volatility changes.

When using bands with indicators, it's usually necessary to adjust the default parameter values. For a 14-day RSI, a 50-day moving average and 2.1 standard deviations work well.

Choose a moving average which follows the position of the indicator. When the indicator is in the upper, middle, or lower part of its range, the moving average should be also. Start with 2 standard deviations and adjust to contain 85 to 90 percent of the indicator.

Used this way, the Bollinger Bands are the new indication of high and low indicator levels. These new values should give more accurate confirmation of the interaction of prices with their bands.

Another indicator refinement is to transform an indicator with its Bollinger Bands into %b ([indicator - indicator lower band] / [indicator upper band - indicator lower band]}. Then plot %b as a normalized version of the indicator. This process creates an adaptable value which allows comparison to other markets and can be used as a trading system signal.

Day traders can use the same Bollinger Bands techniques as with longer time frames. The only real difference is limited volume indicators.

The charts used are an individual preference, but most will want a tick chart for fine detail. Unless prices are very active, the bid and ask prices should be plotted with the last sale tick prices.

For very active markets, it's acceptable to have the chart cover only a portion of the day, if it would otherwise get too cluttered. Use only the normal trading hours as the chart boundaries to eliminate off-hour gaps.

Bar charts and candlesticks are the preferred format. The time frame should have bars with a reasonable price range. If the last price is usually the high or low on the bar, the time frame is too short to produce good patterns.

Once the shortest time frame is selected, then the intermediate and long-term time frame charts can be added.

Two popular uses of Bollinger Bands in day trading are trading off extremes and volatility breakouts. When prices greatly exceed the bands it can be a signal of an overbought or oversold condition. A trade is then made at the first sign of a reversal. The logical stop is a tick beyond the extreme price. An initial target could be the middle band.

For volatility breakouts, the Bollinger Bands default values are usually reduced. Use a shorter moving average and a smaller band width. A Squeeze is required for the setup and entry is made when price exceeds the upper or lower band. The stop can be either a reentry back between the bands or a Parabolic.

Day trading has unique concerns. Traders have to contend with uneven volume distribution and shifts to different exchanges. Test different volume indicators to see if one is workable for your trading. For the trading sessions you're not directly involved with, keep an eye on activity which may distort the patterns you're working with.

• Bollinger Bands define the relative high and low data values for a specified period
• Relative data values allow comparison across different time periods or securities
• Bollinger Bands can modify indicators to provide better relative values.
• Bollinger Bands should not be used to confirm price action alone since they already use both volatility and trend.
• If multiple indicators are used, they should be unrelated to avoid correlation.
• The formation of M-type tops and W-type bottoms can be analyzed with Bollinger Bands.
• Prices walking up and down Bollinger Bands is a common occurrence.
• In volatility breakout systems, closes outside the Bollinger Bands is a sign of continuation, not reversal.
• The default parameter values of a 20-period moving average and bands set off 2 standard deviations may need to be adjusted for different situations.
• The moving average used should follow the intermediate trend, not the one with the best crossover signals.
• Changes to the moving average period, up or down, should include a higher or lower standard deviation value. If the period is 50, the standard deviation should be 2.1. And if the period is 10, the standard deviation is 1.9.
• To ensure consistency, simple moving averages are used for both the center band and in calculating the standard deviation.
• Small sample sizes and non-normal distribution of stock price changes, makes statistical assumptions about the bands questionable.
• %b can be used to normalize indicators and eliminate fixed signal levels.
• Prices tagging the upper or lower band is not a signal of anything by itself.

To be a successful trader or investor, it's suggested to emulate the traits of Supreme Court justice, Oliver Wendell Holmes, Jr.. In an unemotional and disciplined manner, he judged a case based on the context relative to the law and society. To be Holmes-like, deal with relative relationships not absolutes. Test your ideas to weigh their value and make disciplined decisions in a unemotional way.